initialize

abstract suspend fun initialize()(source)

Initializes the container using its pre-configured dependencies and starts background operations.

This method performs the complete initialization sequence for the KARL container, utilizing the dependencies that were already provided during container creation. The container instance holds references to all required components from when it was built, making parameter passing redundant for the initialization process.

Initialization sequence and coordination:

  1. Storage initialization: Set up data storage and load existing container state

  2. Engine initialization: Initialize learning engine with loaded state

  3. Data source setup: Begin observing interaction events from the data source

  4. Background services: Start periodic tasks, monitoring, and maintenance operations

  5. Health verification: Confirm all components are operational and properly coordinated

Component integration and data flow:

Learning engine integration:

  • Initialize with any previously saved model state from storage

  • Configure learning parameters and algorithms based on user instructions

  • Set up coordination with prediction requests and training operations

  • Establish resource sharing and performance monitoring

Data storage integration:

  • Verify storage accessibility and encryption setup

  • Load existing container state, interaction history, and user preferences

  • Configure automated backup and state persistence schedules

  • Set up data retention policies and cleanup procedures

Data source integration:

  • Begin real-time observation of user interaction events

  • Configure event filtering and preprocessing pipelines

  • Set up backpressure handling and load balancing

  • Establish error handling and recovery mechanisms

Asynchronous operations and lifecycle management:

Background task coordination:

  • Launch learning processes within the container's coroutine scope

  • Set up periodic state persistence and health monitoring

  • Configure resource cleanup and graceful shutdown procedures

  • Establish error recovery and fallback mechanisms

State management:

  • Load and validate existing container state from storage

  • Initialize fresh state for new users or corrupted data scenarios

  • Set up incremental state updates and backup procedures

  • Configure state migration for version upgrades

Error handling and recovery:

  • Implement comprehensive error handling for all initialization phases

  • Provide detailed diagnostic information for troubleshooting

  • Support partial initialization and graceful degradation scenarios

  • Enable retry mechanisms for transient initialization failures

Thread safety and concurrency:

  • Ensure thread-safe initialization even with concurrent method calls

  • Coordinate resource allocation and shared state setup

  • Handle cancellation and cleanup during initialization

  • Support re-initialization after component failures

Performance considerations:

  • Optimize initialization sequence for fastest startup time

  • Support lazy initialization of non-critical components

  • Monitor resource usage during initialization

  • Provide progress indicators for long-running initialization tasks

See also

for learning engine configuration requirements

for storage implementation requirements

for data source implementation patterns

for instruction format and usage

Throws

IllegalStateException

if container is already initialized or in invalid state

InitializationException

if the initialization process cannot be completed

StorageException

if data storage operations fail during initialization

ResourceException

if required resources cannot be allocated